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@article{210176,
        author = {Krish Mohan Muruganandam and Abhishek Panda and Aarabh Raj Singh},
        title = {CPython Internals - Method Resolution Order},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {6},
        pages = {72-82},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=210176},
        abstract = {Method Resolution Order (MRO) is a fundamental component of Python's object model that determines the sequence in which classes are searched for methods and attributes during inheritance. Python 2.2 introduced a new-style class model with an MRO algorithm designed to improve inheritance behavior, but its limitations, particularly the violation of monotonicity, motivated the adoption of C3 linearization in Python 2.3. C3 has since remained the basis of method resolution in modern Python. Understanding the differences between these algorithms provides valuable insight into the evolution of Python's object model and the design principles underlying multiple inheritance.
This research aims to conduct a comparative analysis of Python 2.2's new-style-class MRO algorithm and C3 linearization, focusing on inheritance consistency, monotonicity, method resolution behavior, and computational performance. The study will implement both algorithms in a controlled experimental environment and evaluate their behavior across a range of generated inheritance hierarchies, including deep, wide, and complex multiple-inheritance structures. The evaluation will examine differences in resolution order, violations of inheritance precedence constraints, algorithmic execution time, and memory consumption as hierarchy complexity increases.
The expected outcome is a systematic characterization of the strengths and limitations of both algorithms, supported by experimental measurements and representative inheritance examples. The research will also investigate the relationship between correctness guarantees and computational cost, providing insight into the trade-offs involved in designing method resolution algorithms. By combining historical analysis with algorithmic evaluation, this study seeks to contribute a reproducible framework for comparing inheritance-resolution strategies and a deeper understanding of the design decisions that shaped Python's current object model.},
        keywords = {CPython, Method Resolution Order, C3 Linearization, Multiple Inheritance, Monotonicity, Object Model, Algorithm Analysis.},
        month = {November},
        }